| kim | user_id | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ... | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 0.000000 | 0.890909 | 0.794872 | 0.678571 | 0.909091 | 0.000000 | 0.000000 | 0.000000 | 1.666667 | ... | 0.000000 | 0.000000 | 1.333333 | 0.509091 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 |
| 1 | 1 | 0.000000 | 0.654545 | 0.948718 | 0.821429 | 0.872727 | 0.500000 | 1.000000 | 0.888889 | 2.000000 | ... | 0.555556 | 0.000000 | 0.000000 | 0.763636 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 |
| 2 | 10 | 0.610390 | 0.795567 | 0.755682 | 1.405042 | 0.700855 | 0.714286 | 0.980392 | 0.631360 | 1.289610 | ... | 0.741176 | 0.495238 | 1.161765 | 0.689922 | 0.607397 | 1.322464 | 1.905138 | 1.616667 | 2.933333 | 0.0 |
| 3 | 100 | 0.917749 | 0.637931 | 0.755682 | 1.529412 | 0.934473 | 0.666667 | 0.699346 | 0.582105 | 1.406154 | ... | 0.811765 | 0.658065 | 1.043678 | 0.593093 | 0.601732 | 2.333333 | 2.967033 | 2.750000 | 0.000000 | 0.0 |
| 4 | 1000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | ... | 0.000000 | 0.400000 | 0.000000 | 0.000000 | 0.200000 | 0.000000 | 0.000000 | 0.400000 | 0.000000 | 0.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 2132 | 995 | 0.974638 | 0.814286 | 0.466667 | 1.583908 | 0.805263 | 1.000000 | 1.000000 | 0.875991 | 1.853460 | ... | 0.981538 | 0.463300 | 1.513228 | 0.951261 | 0.724138 | 2.649123 | 3.894737 | 2.525641 | 3.666667 | 0.0 |
| 2133 | 996 | 0.842857 | 0.923977 | 0.563636 | 0.000000 | 0.822222 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | ... | 0.000000 | 0.945455 | 0.000000 | 0.618182 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 |
| 2134 | 997 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | ... | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 |
| 2135 | 998 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | ... | 0.000000 | 0.563636 | 0.000000 | 0.700000 | 0.717949 | 0.000000 | 0.000000 | 2.666667 | 2.333333 | 0.0 |
| 2136 | 999 | 0.948718 | 0.897059 | 0.819048 | 0.000000 | 0.000000 | 0.500000 | 0.750000 | 0.000000 | 0.000000 | ... | 1.000000 | 0.000000 | 0.000000 | 0.834835 | 0.509091 | 0.000000 | 0.000000 | 2.321429 | 0.000000 | 0.0 |
2137 rows × 25 columns
| kim | user_id | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ... | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 0.0 | 10.0 | 12.0 | 7.0 | 10.0 | 0.0 | 0.0 | 0.0 | 2.0 | ... | 0.0 | 0.0 | 2.0 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1 | 1 | 0.0 | 10.0 | 12.0 | 7.0 | 10.0 | 4.0 | 3.0 | 8.0 | 6.0 | ... | 9.0 | 0.0 | 0.0 | 10.0 | 0.0 | 1.0 | 5.0 | 0.0 | 0.0 | 0.0 |
| 2 | 10 | 21.0 | 28.0 | 32.0 | 34.0 | 26.0 | 6.0 | 17.0 | 95.0 | 55.0 | ... | 34.0 | 20.0 | 16.0 | 42.0 | 37.0 | 23.0 | 22.0 | 15.0 | 5.0 | 0.0 |
| 3 | 100 | 21.0 | 28.0 | 32.0 | 34.0 | 26.0 | 5.0 | 17.0 | 75.0 | 25.0 | ... | 34.0 | 30.0 | 29.0 | 36.0 | 21.0 | 21.0 | 13.0 | 7.0 | 0.0 | 0.0 |
| 4 | 1000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 10.0 | 0.0 | 13.0 | 10.0 | 0.0 | 0.0 | 4.0 | 0.0 | 0.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 2132 | 995 | 23.0 | 20.0 | 20.0 | 29.0 | 19.0 | 4.0 | 14.0 | 65.0 | 66.0 | ... | 25.0 | 54.0 | 27.0 | 34.0 | 29.0 | 18.0 | 19.0 | 12.0 | 5.0 | 0.0 |
| 2133 | 996 | 20.0 | 18.0 | 10.0 | 0.0 | 9.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 10.0 | 0.0 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2134 | 997 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2135 | 998 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 10.0 | 0.0 | 15.0 | 12.0 | 0.0 | 0.0 | 6.0 | 5.0 | 0.0 |
| 2136 | 999 | 12.0 | 16.0 | 14.0 | 0.0 | 0.0 | 3.0 | 7.0 | 0.0 | 0.0 | ... | 8.0 | 0.0 | 0.0 | 36.0 | 10.0 | 0.0 | 0.0 | 7.0 | 0.0 | 0.0 |
2137 rows × 25 columns
| vk | point | user_id | |
|---|---|---|---|
| 0 | https://vk.com/id455460735 | 3 | 1505 |
| 1 | https://vk.com/id575165735 | 3 | 959 |
| 2 | https://vk.com/id191766636 | 3 | 814 |
| 7 | https://vk.com/id471957172 | 3 | 1991 |
| 8 | https://vk.com/id542247727 | 3 | 1638 |
| ... | ... | ... | ... |
| 738 | https://vk.com/id183562702 | 5 | 439 |
| 739 | https://vk.com/id247848204 | 5 | 233 |
| 740 | https://vk.com/id277072159 | 5 | 1823 |
| 741 | https://vk.com/id390463571 | 5 | 520 |
| 742 | https://vk.com/id330302671 | 5 | 816 |
507 rows × 3 columns
| count | quality | point | predict | correct | dif | |
|---|---|---|---|---|---|---|
| 0 | 574.0 | 28.878723 | 5 | 5 | True | 0 |
| 1 | 294.0 | 17.818278 | 4 | 5 | False | -1 |
| 2 | 544.0 | 21.496513 | 5 | 5 | True | 0 |
| 3 | 10.0 | 0.400000 | 4 | 4 | True | 0 |
| 4 | 234.0 | 23.711307 | 5 | 5 | True | 0 |
| ... | ... | ... | ... | ... | ... | ... |
| 97 | 60.0 | 10.155760 | 5 | 5 | True | 0 |
| 98 | 102.0 | 8.164629 | 4 | 5 | False | -1 |
| 99 | 20.0 | 3.175758 | 5 | 4 | False | 1 |
| 100 | 114.0 | 14.922303 | 5 | 5 | True | 0 |
| 101 | 631.0 | 20.052706 | 5 | 5 | True | 0 |
102 rows × 6 columns
Всего 72 наблюдения, в которых ученик решал достаточное количество задач (выше 60) Из них 55 наблюдения предсказаны верно В 52 верных наблюдениях предсказаны 5-ки В 12 наблюдениях предсказан результат на 1 выше, чем получен учеником В 1 наблюдениях предсказан результат на 2 выше, чем получен учеником В 4 наблюдениях предсказан результат на 1 ниже, чем получен учеником В 0 наблюдениях предсказан результат на 2 ниже, чем получен учеником
| tsne_1 | tsne_2 | sums | user_id | point | |
|---|---|---|---|---|---|
| 0 | -7.372083 | 12.315699 | 70.0 | 0 | 4 |
| 1 | 24.167839 | 22.652206 | 686.0 | 10 | 5 |
| 2 | 14.397183 | 17.087486 | 582.0 | 100 | 5 |
| 3 | 17.795519 | 1.515710 | 173.0 | 1005 | 5 |
| 4 | 0.442748 | 3.382986 | 135.0 | 1008 | 5 |
| ... | ... | ... | ... | ... | ... |
| 502 | 9.448067 | 9.205212 | 330.0 | 988 | 5 |
| 503 | 26.116951 | 27.506800 | 745.0 | 99 | 5 |
| 504 | -2.803667 | -12.704346 | 20.0 | 991 | 4 |
| 505 | 24.661732 | 28.788927 | 605.0 | 995 | 4 |
| 506 | -20.161539 | -5.510995 | 77.0 | 996 | 4 |
507 rows × 5 columns
Результаты моделей на основе специальных данных
| acc | ac_5 | ac_4 | ac_3 | up_pred | down_pred | |
|---|---|---|---|---|---|---|
| model | ||||||
| cb | 0.727381 | 0.948191 | 0.055780 | -0.05 | 0.233333 | 0.039286 |
| dt | 0.711905 | 0.913516 | 0.113010 | -0.05 | 0.221429 | 0.066667 |
| gb | 0.666071 | 0.834001 | 0.177311 | -0.05 | 0.196429 | 0.137500 |
| rf | 0.704762 | 0.900351 | 0.123417 | -0.05 | 0.219048 | 0.076190 |
Проясним немного особенности метрик моделей:
Text(0, 0.5, 'Точность/доля')